Inflammatory stimuli up-regulate transient receptor potential vanilloid-1 expression in human bronchial fibroblasts
Bibliographic record
Abstract
Lung fibroblasts are involved in interstitial lung disease, chronic asthma, and chronic obstructive pulmonary disease (COPD). The expanded fibroblast population in airway disease leads to airway remodeling and contributes to the inflammatory process seen in these diseases. The cation channel transient receptor potential vanilloid-1 (TRPV1) is activated by noxious stimuli, including capsaicin, protons, and high temperatures and is thought to have a role in inflammation. Although TRPV1 expression is primarily reported to be neuronal, some extraneuronal expression has been reported. The authors therefore sought to determine whether human primary bronchial fibroblasts (HPBFs) express TRPV1 and whether inflammatory mediators can induce TRPV1 expression. The authors show that fibroblasts are predominantly TRPV1 negative; however, following stimulation with 3 common inflammatory mediators, tumor necrosis factor α (TNF-α), lipopolysaccharide (LPS), and interleukin-1α (IL-1α), TRPV1 mRNA was observed at 24 and 48 hours post treatment with all 3 mediators. Using Western blotting an increase in TRPV1 expression with all 3 inflammatory mediators was detected with significant increases seen at 72 hours post LPS and IL-1α treatment. In stark contrast to the untreated fibroblasts, significant calcium signaling in response to capsaicin and resiniferatoxin in HPBFs treated for 24 and 48 hours with TNF-α, LPS, or IL-1α was also observed. These results indicate that TRPV1 can be expressed on bronchial fibroblasts in situations where an underlying inflammatory stimulus exists, as is the case in airway diseases such as asthma and COPD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".